diff --git a/nemo/nemo/core/neural_modules.py b/nemo/nemo/core/neural_modules.py
index 24b4efb938a5..1ab63787bc68 100644
--- a/nemo/nemo/core/neural_modules.py
+++ b/nemo/nemo/core/neural_modules.py
@@ -216,8 +216,12 @@ def __call__(self, **kwargs):
                 )
 
             # Creating ad-hoc class for returning from module's forward pass.
+            output_class_name = f'{self.__class__.__name__}Output'
             field_names = list(output_port_defs)
-            result_type = collections.namedtuple('NmOutput', field_names)
+            result_type = collections.namedtuple(
+                typename=output_class_name,
+                field_names=field_names,
+            )
 
             # Tie tuple of output tensors with corresponding names.
             result = result_type(*result)
diff --git a/tests/test_pytorch_trainers.py b/tests/test_pytorch_trainers.py
index cd3d1e851a53..77baeb3bb27e 100644
--- a/tests/test_pytorch_trainers.py
+++ b/tests/test_pytorch_trainers.py
@@ -33,6 +33,11 @@ def test_simple_train_named_output(self):
         loss = nemo.backends.pytorch.tutorials.MSELoss()
 
         data = data_source()
+        self.assertEqual(
+            first=type(data).__name__,
+            second='RealFunctionDataLayerOutput',
+            msg='Check output class naming coherence.',
+        )
         y_pred = trainable_module(x=data.x)
         loss_tensor = loss(predictions=y_pred, target=data.y)